What Is Agentic RAG?
Agentic Retrieval-Augmented Generation combines traditional RAG techniques with autonomous decision-making. In standard RAG, an AI retrieves relevant data and generates a response; in agentic RAG, the system actively determines what information to seek, how to interpret it, and when to act on it. This approach blends retrieval, reasoning, memory, and planning to produce more context-aware and goal-driven outputs. In enterprise workflows, agentic RAG ensures AI outputs are not only accurate but actionable in complex, evolving scenarios.